Instructions to use dx8152/Flux2-Klein-9B-Consistency with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dx8152/Flux2-Klein-9B-Consistency with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dx8152/Flux2-Klein-9B-Consistency") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Update README.md
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README.md
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----- 2026/4/17 V2 version update ----
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This time, I systematically break down how to train the Klein model, including dataset creation strategies and a detailed training tutorial: [https://youtu.be/j6dqOekUQ8c](https://youtu.be/j6dqOekUQ8c)
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Cloud training — sign up to get two free 3-hour RTX 5090 vouchers: [https://studio.aigate.cc/images/993593021914284032?channel=R6P1L7N3J](https://studio.aigate.cc/images/993593021914284032?channel=R6P1L7N3J)
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----- 2026/4/17 V2 version update ----
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This time, I systematically break down how to train the Klein model, including dataset creation strategies and a detailed training tutorial: [https://youtu.be/j6dqOekUQ8c](https://youtu.be/j6dqOekUQ8c)
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Cloud training — sign up to get two free 3-hour RTX 5090 vouchers: [https://studio.aigate.cc/images/993593021914284032?channel=R6P1L7N3J](https://studio.aigate.cc/images/993593021914284032?channel=R6P1L7N3J)
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